Detecting compromised social media accounts by analyzing affinity groups

ABSTRACT

Devices and methods for detecting a compromised social media account are disclosed. A method includes: receiving, by a computing device, social media content corresponding to a plurality of social media accounts; determining, by the computing device, a plurality of affinity groups, each including two or more social media accounts from the plurality of social media accounts, based upon the received social media content; determining, by the computing device, whether or not a particular social media account of the plurality of social media accounts is compromised using the received social media content and the determined plurality of affinity groups; and in response to determining that the particular social media account is compromised, the computing device providing a notification indicating that the particular social media account is compromised.

BACKGROUND

The present invention generally relates to computing devices and, moreparticularly, to a system and method for detecting compromised socialmedia accounts by analyzing affinity groups.

Hacking social media accounts, where an unauthorized user compromises(e.g., obtains control of) a social media account that is owned byanother user, is increasingly common. Hacked social media accounts areoften used to distribute malicious content. For example, hacked socialmedia accounts may be used to publish malicious content (or linksthereto) such as phishing websites (e.g., websites that falsely purportto be from reputable companies and that are designed to induce visitorsto reveal personal information) or malware (e.g., virus-infected files).Hacked social media accounts may also be used to publish other types ofmalicious content designed to steal a user's personal or financialinformation, steal corporate secrets, damage a computing device, and/ordamage a user's files on a computing device. Additionally, hacked socialmedia accounts may be used to publish content (or links thereto) that isfraudulent (e.g., false advertising) or libelous.

Various approaches have been used to detect compromised social mediaaccounts, including historical analysis and content analysis. In thehistorical analysis approach, new content posted by a social mediaaccount is correlated with content previously posted by that socialmedia account. If there is not sufficient correlation between the newcontent and the previously posted content, the social media account maybe identified as a potentially compromised account. In the contentanalysis approach, postings by a social media account are classifiedbased upon a type or nature of the posted content. If the posted contentis determined to meet predetermined criteria, the social media accountmay be identified as a potentially compromised account.

SUMMARY

In a first aspect of the invention, there is a method that includes:receiving, by a computing device, social media content corresponding toa plurality of social media accounts; determining, by the computingdevice, a plurality of affinity groups, each including two or moresocial media accounts from the plurality of social media accounts, basedupon the received social media content; determining, by the computingdevice, whether or not a particular social media account of theplurality of social media accounts is compromised using the receivedsocial media content and the determined plurality of affinity groups;and in response to determining that the particular social media accountis compromised, the computing device providing a notification indicatingthat the particular social media account is compromised.

In another aspect of the invention, there is a computer program productthat includes a computer readable storage medium having programinstructions embodied therewith. The program instructions are executableby a computing device to cause the computing device to: receive socialmedia content corresponding to a plurality of social media accountsacross a plurality of social media networks; determine a plurality ofaffinity groups based upon the received social media content; determinewhether or not a particular social media account of the plurality ofsocial media accounts is compromised using the received social mediacontent and the determined plurality of affinity groups; and in responseto determining that the particular social media account is compromised,provide a notification indicating that the particular social mediaaccount is compromised.

In another aspect of the invention, there is a system that includes: ahardware processor, a computer readable memory, and a computer readablestorage medium associated with a computer device; program instructionsof a social media content receiver configured to receive social mediacontent corresponding to a plurality of social media accounts across aplurality of social media networks; program instructions of an affinitygroup determiner configured to determine a plurality of affinity groups,each including two or more social media accounts from the plurality ofsocial media accounts, based upon the received social media content; andprogram instructions of a compromised account determiner configured todetermine whether or not a particular social media account of theplurality of social media accounts is compromised using the receivedsocial media content and the determined plurality of affinity groups.The compromised account determiner, in response to determining that theparticular social media account is compromised, is configured to providea notification indicating that the particular social media account iscompromised.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described in the detailed description whichfollows, in reference to the noted plurality of drawings by way ofnon-limiting examples of exemplary embodiments of the present invention.

FIG. 1 depicts a cloud computing node in accordance with aspects of theinvention.

FIG. 2 depicts a cloud computing environment in accordance with aspectsof the invention.

FIG. 3 depicts abstraction model layers in accordance with aspects ofthe invention.

FIG. 4 depicts an illustrative environment in accordance with aspects ofthe invention.

FIG. 5 depicts a block diagram of an exemplary program module inaccordance with aspects of the invention.

FIG. 6 depicts a plurality of points in n-dimensional space occupied bya plurality of social media accounts according to an example.

FIG. 7 depicts exemplary methods in accordance with aspects of theinvention.

DETAILED DESCRIPTION

Significant harm may result from the hacking of social media accounts.By using hacked social media accounts, individuals or organizations maybe able to anonymously distribute malicious content and avoididentification by social media network operators and/or governmentalentities. The publication of malicious content may cause damage to othersocial media users through information theft, damage to files, and/ordamage to computing devices. Additionally, reputational damage may beinflicted on owners of hacked social media accounts. Early detection ofhacked social media accounts may help a social media account owner, asocial media network operator, and/or governmental entities to moreeffectively mitigate this harm.

The present invention generally relates to computing devices and, moreparticularly, to a system and method for detecting compromised socialmedia accounts by analyzing affinity groups. Aspects of the inventionare directed to detecting compromised social media accounts by analyzingaffinity groups. Compromised social media accounts may be moreaccurately detected as compared to the historical analysis approach andthe content analysis approach, thereby minimizing false positives (e.g.,uncompromised social media accounts that are identified as potentiallycompromised) and false negatives (e.g., compromised social media accountthat are not identified as potentially compromised).

As described herein, aspects of the invention may include gatheringinformation and content from social media accounts or users acrossmultiple social media networks or platforms and analyzing the gatheredinformation and content to identify multiple affinity groups or peergroups. Affinity groups or peer groups may include a plurality of socialmedia accounts associated with a plurality of people that are linkedtogether by shared elements or attributes. These shared elements mayinclude demographic data (e.g., similar age, place of birth, date ofbirth, city, etc.), interests (e.g., an interest in a particular sportsteam, as determined based on “likes,” subscriptions, and “follows”), andpersonality (e.g., as determined from posts).

Other aspects of the invention may include correlating new social mediaposts of an account or user with historical posts by the same account oruser as well as historical posts from other accounts or users who are inone or more of the same affinity groups as the user and determiningwhether or not the social media account of the user is potentiallycompromised based on the correlation.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as Follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a nonremovable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and compromised social media accountdetection 96.

Referring back to FIG. 1, the program/utility 40 may include one or moreprogram modules 42 that generally carry out the functions and/ormethodologies of embodiments of the invention as described herein (e.g.,such as the functionality provided by compromised social media accountdetection 96). Specifically, the program modules 42 may gatherinformation and content from social media accounts or users acrossmultiple social media networks or platforms, analyze the gatheredinformation and content to identify multiple affinity or peer groups,correlate new social media posts of an account or user with historicalposts by the same account or user as well as historical posts from otheraccounts or users who are in one or more of the same peer groups as theaccount or user, and determine whether or not the social media accountof the user is potentially compromised based on the correlation. Otherfunctionalities of the program modules 42 are described further hereinsuch that the program modules 42 are not limited to the functionsdescribed above. Moreover, it is noted that some of the modules 42 canbe implemented within the infrastructure shown in FIGS. 1-3. Forexample, the modules 42 may be representative of a compromised accountdetection program module 420 as shown in FIGS. 4 and 5.

FIG. 4 depicts an illustrative environment 400 in accordance withaspects of the invention. As shown, environment 400 comprises a server410 which communicates via a computer network 440 with a first socialmedia network server 430-1, a second social media network server 430-2,and an n-th social media network server 430-n. The network 440 may beany suitable network such as a LAN, WAN, or the Internet. The server410, the first social media network server 430-1, the second socialmedia network server 430-2, and the n-th social media network server430-n may be physically collocated, or may be situated in separatephysical locations.

The server 410 may be a server 12 shown in FIG. 1 and may be situated inthe cloud computing environment 50 at one or more of the nodes 10 shownin FIG. 2. The server 410 may be implemented as hardware and/or softwareusing components such as mainframes 61; RISC (Reduced Instruction SetComputer) architecture based servers 62; servers 63; blade servers 64;storage devices 65; networks and networking components 66; virtualservers 71; virtual storage 72; virtual networks 73, including virtualprivate networks; virtual applications and operating systems 74; andvirtual clients 75 shown in FIG. 3.

The first social media network server 430-1, the second social medianetwork server 430-2, and the n-th social media network server 430-n mayalso be situated in the cloud computing environment 50 on one or more ofthe nodes 10 shown in FIG. 2. The first social media network server430-1, the second social media network server 430-2, and the n-th socialmedia network server 430-n may be implemented as hardware and/orsoftware using components such as mainframes 61; RISC (ReducedInstruction Set Computer) architecture based servers 62; servers 63;blade servers 64; storage devices 65; networks and networking components66; virtual servers 71; virtual storage 72; virtual networks 73,including virtual private networks; virtual applications and operatingsystems 74; and virtual clients 75 shown in FIG. 3.

According to an embodiment, the server 410 may include a compromisedaccount detection program module 420, which may include hardware and/orsoftware and may be one or more of the program modules 42 shown inFIG. 1. According to an embodiment, the compromised account detectionprogram module 420 includes program instructions for executing acompromised account detection program. The program instructions includedin the compromised account detection program module 420 of the server410 may be executed by one or more hardware processors. According to anembodiment, the compromised account detection program performs functionsrelated to detecting compromised social media accounts, as discussedbelow. The compromised account detection program may also perform otherfunctions, for example, taking actions in response to detectingcompromised social media accounts (e.g., disabling, locking, orotherwise blocking use of the compromised social media accounts).

According to embodiment, the compromised account detection program ofthe compromised account detection program module 420 may function to:(1) gather information and content from social media accounts or usersacross multiple social media networks or platforms including from thefirst social media network server 430-1, the second social media networkserver 430-2, and the n-th social media network server 430-n; (2)analyze the gathered information and content to identify multipleaffinity or peer groups; (3) correlate new social media posts of anaccount or user with historical posts by the same account or user aswell as historical posts from other accounts or users who are in one ormore of the same peer groups as the user; and (4) determine whether ornot the social media account of the user is potentially compromisedbased on the correlation.

FIG. 5 shows a block diagram of an exemplary compromised accountdetection program module 420 in the server 410 (of FIG. 4) in accordancewith aspects of the invention. In embodiments, the compromised accountdetection program module 420 includes a social media information andcontent gatherer 500, an affinity group identifier 510, a new socialmedia post analyzer 520, and a compromised account detector 530.

In embodiments, the social media information and content gatherer 500gathers social media information and content related to a plurality ofsocial media accounts. For a particular social media account, the socialmedia information gathered may include, but is not limited to, InternetProtocol (IP) addresses, geolocation data, account creation date andtime, numbers and/or identities of social media “friends” or“followers,” and types of information posted. Additionally, for aparticular social media account, the social media content gathered byinclude, but is not limited to, content posted by the social mediaaccount, content published at external websites that are linked to bythe social media account, and/or profile content associated with thesocial media account.

According to an embodiment, the social media information and contentgatherer 500 requests the social media information and content relatedto the plurality of social media accounts from one or more social medianetworks. For example, the social media information and content gatherer500 may send one or more requests to the first social media networkserver 430-1, the second social media network server 430-2, and the n-thsocial media network server 430-n for the social media information andcontent related to the plurality of social media accounts. The socialmedia information and content gatherer 500 may use Simple Object AccessProtocol (SOAP) to request and obtain the social media information andcontent related to the plurality of social media accounts from webservices running on the first social media network server 430-1, thesecond social media network server 430-2, and the n-th social medianetwork server 430-n.

Alternatively, according to an embodiment, the social media informationand content gatherer 500 may use one or more Application ProgrammingInterfaces (APIs) of the one or more social media networks to requestand obtain the social media information and content related to theplurality of social media accounts. According to another embodiment, thesocial media information and content gatherer 500 may use any other APIor protocol to request and obtain the social media information andcontent related to the plurality of social media accounts.

The social media information and content gatherer 500 may request andobtain historical content, including social media information andcontent related to the plurality of social media accounts from one ormore social media networks that was posted during a predeterminedhistorical time period. This historical content requested and obtainedby the social media information and content gatherer 500 may be used bythe affinity group identifier 510 to identify affinity groups asdescribed herein.

Additionally, the social media information and content gatherer 500 mayrequest and obtain newly posted content including social mediainformation and content related to the plurality of social mediaaccounts from one or more social media networks. For example, the newlyposted content requested and obtained by the social media informationand content gatherer 500 may be social media information and contentthat was posted after a date and time when social media information andcontent was last requested and obtained by the social media informationand content gatherer 500. This newly posted content requested andobtained by the social media information and content gatherer 500 may beanalyzed by the new social media post analyzer 520 as described herein.

In embodiments, the affinity group identifier 510 determines one or moreaffinity groups for each of the plurality of social media accounts.According to an embodiment, the affinity group identifier 510 analyzesthe social media information and content gathered by the social mediainformation and content gatherer 500 to determine a set of affinity orpeer groups. For example, the affinity group identifier 510 maydetermine a set of affinity groups based on age, interest in sports,employment, number of friends, identities of friends, identities offamily members, “liked” pages, subscribed pages, or any other dimensionsin the social media information and content related to the plurality ofsocial media accounts.

According to an embodiment, the affinity group identifier 510 may beconfigured to identify affinity groups based upon one or morepredetermined dimensions (e.g., age) in the data requested and obtainedby the social media information and content gatherer 500. The affinitygroup identifier 510 may use natural language processing (NLP)techniques to analyze the social media information and content gatheredby the social media information and content gatherer 500 to determine,for each of the plurality of social media accounts, data associated withthe one or more predetermined dimensions. For example, the affinitygroup identifier 510 may use natural language processing techniques toidentify profile data indicating an age and/or content indicating an age(e.g., a message wishing the user a happy 50^(th) birthday).

The affinity group identifier 510 may then assign each of the pluralityof social media accounts to one or more affinity groups based on thedetermined data associated with the one or more predetermineddimensions. According to an embodiment, the affinity groups associatedwith one or more dimensions may be predetermined. For example, for theage dimension, there may be a predetermined set of age-based affinitygroups corresponding to predetermined age ranges. For each of theplurality of social media accounts, the affinity group identifier 510may use the determined data associated with the dimension to assign thesocial media account to one or more affinity groups in the dimension.For example, the affinity group identifier 510 may use profileinformation indicating an age of 25 to assign the social media accountto an “age 21-25” affinity group.

According to an embodiment, the affinity group identifier 510 scores orranks each social media account with respect to one or more dimensionsbased upon the determined data. The affinity group identifier 510 mayrank the social media accounts based upon identified data associatedwith dimensions including a number of posts containing content relatedto a particular subject, a number of posts related to the particularsubject liked on a social media network, and a count of social medianetwork groups related to the particular subject of which the socialmedia account is a member.

For example, the affinity group identifier 510 may determine socialmedia accounts that are members of an online role-playing game affinitygroup. Members of this affinity group may have a high affinity towardsonline role-playing games. For each of a plurality of social mediaaccounts, the affinity group identifier 510 may identify data associatedwith various dimensions (e.g., shared posts containing content relatedto online role-playing games, online role-playing games liked on asocial media network, and social media network groups related to onlinerole-playing games of which the social media account is a member). Theaffinity group identifier 510 may rank each social media account withrespect to each of the various dimensions based upon the identifieddata. For example, the social media accounts may be ranked with respectto each of the various dimensions based upon identified data including anumber of shared posts containing content related to online role-playinggames, a number of online role-playing games liked on a social medianetwork, and a count of social media network groups related to onlinerole-playing games of which the social media account is a member.

According to an embodiment, the affinity group identifier 510 isconfigured (e.g., programmed) to determine a point in n-dimensionalspace occupied by each social media account based upon a score or rankassigned to the social media account by the affinity group identifier510 for each of the n dimensions. The affinity group identifier 510 mayanalyze a distribution of the plurality of social media accounts inn-dimensional space to determine regions in the n-dimensional spaceoccupied by a high density of social media accounts. The affinity groupidentifier 510 may determine that all of the social media accountsoccupying a particular region in the n-dimensional space are members ofa particular affinity group. According to an embodiment, the affinitygroup identifier 510 determines a centroid of a particular regionoccupied by a high density of social media accounts and determines thatall social media account that are within a predetermined distance of thecentroid are members of a particular affinity group. The affinity groupidentifier 510 may determine the distance between a social mediaaccount's position in n-dimensional space and the position of thecentroid in the n-dimensional space using a Euclidean distance or usingany other metric.

According to an embodiment, the affinity group identifier 510 isconfigured (e.g., programmed) to determine a closeness value for aparticular social media account with respect to a particular affinitygroup of which the particular social media account is a member, based onthe Euclidian distance (or the distance determined using any othermetric) between the particular social media account's position in then-dimensional space and the position in the n-dimensional space of thecentroid of the affinity group. The closeness value may be in the range0.0 to 1.0. For each social media account, the affinity group identifier510 may store a plurality of affinity groups of which the social mediaaccount is a member, as determined by the affinity group identifier 510,as well as a closeness value determined by the affinity group identifier510 for each affinity group of which the social media account is amember. The affinity group identifier 510 may store this information ina central user profile database system as tags and associated metadata(e.g., a date of a last profile update).

For example, a first social media account having a comparatively highernumber of shared posts containing content related to online role-playinggames, online role-playing games liked on a social media network, andsocial media network groups related to online role-playing games ofwhich the social media account is a member and a second social mediaaccount having a comparatively lower number of the aforementioned posts,likes, and memberships may both be determined to be members of an onlinerole-playing game affinity group. However, the first social mediaaccount may have a closeness value indicating that the first socialmedia account is comparatively closer to the centroid of the onlinerole-playing game affinity group as compared to that of the secondsocial media account.

According to an embodiment, if there is no data determined to beassociated with particular dimensions for a particular social mediaaccount, or if a level of confidence in the determined data is below apredetermined threshold (e.g., the data cannot be determined tocorrespond to a particular dimension), the affinity group identifier 510may not assign the particular social media account to any affinity groupassociated with the particular dimensions. Additionally, if the distancebetween the point in n-dimensional space occupied by the social mediaaccount and the centroids of affinity groups associated with theparticular dimensions exceeds a predetermined distance, the affinitygroup identifier 510 may not assign the particular social media accountto any affinity group associated with the particular dimensions.

Alternatively, if the identified data associated with the particulardimensions for a particular social media account corresponds to two ormore affinity groups associated with the particular dimensions, theaffinity group identifier 510 may assign the particular social mediaaccount to two or more affinity groups associated with the particulardimensions if the distance between the point in n-dimensional spaceoccupied by the social media account and the centroids of the two ormore affinity groups does not exceed a predetermined distance. Accordingto another embodiment, the affinity group identifier 510 may assign theparticular social media account to the affinity group associated withthe particular dimensions to which the distance between the point inn-dimensional space occupied by the social media account and thecentroid of the affinity group is smallest.

According to another embodiment, a k-means technique may be used topartition the plurality of social media accounts into a plurality ofaffinity groups for each of one or more dimensions. For example, thek-means technique may be used to assign each of the plurality of socialmedia accounts to one or more of a predetermined number of affinitygroups associated with one or more dimensions based upon the identifieddata associated with the dimension and Euclidian distances or otherdistances calculated between points in n-dimensional space occupied byeach social media account based upon a score or rank assigned to thesocial media account by the affinity group identifier 510 for each ofthe n dimensions. According to still another embodiment, instead ofusing a predetermined number of affinity groups for a dimension, theaffinity group identifier 510 may dynamically determine a set ofaffinity groups for a dimension based upon clusters of social mediaaccounts in n-dimensional space determined using the k-means technique.According to yet another embodiment, a silhouette measure may be used todetermine the plurality of affinity groups for each of one or moredimensions.

The social media information and content gatherer 500 may gather updatedsocial media information and content at predetermined time intervals,and the affinity group identifier 510 may use the updated social mediainformation and content to update membership of the plurality of socialmedia accounts in the plurality of affinity groups. For example, thesocial media information and content gatherer 500 may gather updatedsocial media information and content in real time on a nightly or weeklybasis, and the affinity group identifier 510 may use the updated socialmedia information and content to determine or update affinity groupmembership as described herein for each of the plurality of social mediaaccounts in real time or on a nightly or weekly basis. Additionally, theaffinity group identifier 510 may recalculate the closeness values basedon the updated social media information and content gathered by thesocial media information and content gatherer 500.

Alternatively, the social media information and content gatherer 500 maygather updated social media information and content at intervals basedupon the amount of posted content, a number of newly created socialmedia accounts, or any other factor. In another embodiment, the socialmedia information and content gatherer 500 may gather updated socialmedia information and content in response to a manual request. Socialmedia accounts created between a current update and a previous updatemay also be classified by the affinity group identifier 510 as discussedabove.

Still referring to FIG. 5, in embodiments, the new social media postanalyzer 520 analyzes new social media posts. According to anembodiment, the new social media post analyzer 520 analyzes the newlyposted social media information and content (e.g., new posts) gatheredby the social media information and content gatherer 500. The new socialmedia post analyzer 520 scores each new post based on a correlation withother posts (e.g., earlier posts) made by the same social media accountas well as posts made by other social media accounts that are members ofone or more of the same affinity groups as the social media account. Thescore may represent a likelihood of the post having been made by anowner of the social media account.

According to an embodiment, the new social media post analyzer 520analyzes a new social media post by comparing content in the new socialmedia post with content in other posts (e.g., earlier posts) made by thesame social media account as well as content in posts made by othersocial media accounts that are members of one or more of the sameaffinity groups as the social media account. The new social media postanalyzer 520 may determine individual content entities including links,pictures, and text in the new social media post. For each individualcontent entity, the new social media post analyzer 520 compares thecontent entity to content in posts made by other members of the affinitygroups of which the social media account is a member.

The new social media post analyzer 520 may determine a sub-score foreach content entity in the new social media post based upon a number ofexact or near matches with content in posts made by other members of theaffinity groups of which the social media account is a member. Acomparatively higher sub-score may be assigned to a content entity inthe new social media post that matches a comparatively larger number ofitems of content in posts made by other members of the affinity groupsof which the social media account is a member, and a comparatively lowersub-score may be assigned to a content entity in the new social mediapost that matches a comparatively smaller number of items of content inposts made by other members of the affinity groups of which the socialmedia account is a member. A comparatively higher score may indicatethat a content entity is more in context with content posted by othermembers of the affinity groups of which the social media account is amember and therefore more likely to be posted by an owner of the socialmedia account, and a comparatively lower score may indicate a contententity is less in context with content posted by other members of theaffinity groups of which the social media account is a member andtherefore more likely to be posted by someone other than an owner of thesocial media account (e.g., posted by a compromised account). Accordingto another embodiment, in determining the sub-score for each contententity in the new social media post, the new social media post analyzer520 may also compare the content entities to the content of news sites,blogs, and other websites associated with (e.g., linked to by) membersof the affinity groups of which the social media account is a member.

The new social media post analyzer 520 may determine an overall scorefor the new social media post based on one or more sub-scores for one ormore content entities in the new social media post. The new social mediapost analyzer 520 may determine the overall score as an average of thesub-scores for the one or more content entities in the new social mediapost. Alternatively, the new social media post analyzer 520 maydetermine the overall score based on a lowest sub-score or a highestsub-score among the sub-scores for the one or more content entities inthe new social media post. According to an embodiment, a comparativelyhigher overall score determined by the new social media post analyzer520 may represent a comparatively higher likelihood that the post wasmade by an owner of the social media account, and a comparatively loweroverall score determined by the new social media post analyzer 520 mayrepresent a comparatively lower likelihood that the post was made by anowner of the social media account.

According to an alternative embodiment, the new social media postanalyzer 520 may, for a new social media post, determine a separatescore for each affinity group of which the social media account is amember. In this embodiment, the new social media post analyzer 520 maydetermine an overall score for the new social media post using aweighted average of the scores for each affinity group, where theweighting is based upon the social media account's closeness value forthe affinity group. In this manner, the new social media post analyzer520 accords more weight to scores for affinity groups having centroidsto which the social media account is closer.

Still referring to FIG. 5, in embodiments, the compromised accountdetector 530 determines whether or not a social media account is likelyto be a compromised account based on an overall score for one or morenew social media posts determined by the new social media post analyzer520. The compromised account detector 530 may determine that a socialmedia account is likely to be a compromised account if the overall scorefor a new social media post determined by the new social media postanalyzer 520 is lower than a predetermined threshold.

According to another embodiment, the compromised account detector 530may determine that a social media account is likely to be a compromisedaccount if the overall score for each of a predetermined number of newsocial media posts is lower than a predetermined threshold. According toyet another embodiment, the compromised account detector 530 maydetermine that a social media account is likely to be a compromisedaccount if the overall score for any one new social media postdetermined by the new social media post analyzer 520 is lower than afirst predetermined threshold or if the overall score for each of apredetermined number of new social media posts is lower than a secondpredetermined threshold that is higher than the first predeterminedthreshold. The predetermined thresholds may be adjusted to reduce anumber of social media accounts incorrectly determined to be likely tobe compromised or to reduce a number of compromised social mediaaccounts that are not determined to be likely to be compromised.

In response to determining that a social media account is likely to becompromised, the compromised account detector 530 may trigger anotification to be made to an account owner of the social media account,a social media network operator, or to the social media network orplatform associated with the account. For example, a push notificationmay be sent to a mobile device of an account owner of the social mediaaccount. In response to determining that a social media account islikely to be compromised, the compromised account detector 530 may takeother actions, including preventing additional posts from being made bythe social media account, deleting or hiding posts made by the socialmedia account after the account is determined to be likely to becompromised, restricting access to the social media account, or lockingthe social media account.

According to an embodiment, the compromised account detector 530 mayreceive feedback regarding whether or not the social media account thatwas determined to be likely to be compromised was actually compromised.The predetermined thresholds used by the compromised account detector530 may be adjusted based on the feedback received to reduce a number ofsocial media accounts incorrectly determined to be likely to becompromised or a number of compromised social media accounts that arenot determined to be likely to be compromised.

FIG. 6 depicts a plurality of points in n-dimensional space occupied bya plurality of social media accounts according to an example, asdetermined by the affinity group identifier 510, discussed above. Thehorizontal axis in FIG. 6 represents a first dimension, and the verticalaxis represents a second dimension. As illustrated in FIG. 6, the socialmedia accounts may be clustered in several high-density regions. Theaffinity group identifier 510 may determine centroids 630, 640, and 650of regions occupied by a high density of social media accounts and maydetermine that all social media accounts that are within a predetermineddistance of the centroid are members of a particular affinity group. Forexample, the affinity group identifier may determine that social mediaaccounts within a predetermined distance 600 of the centroid 630 aremembers of a first affinity group, social media accounts within apredetermined distance 610 of the centroid 640 are members of a secondaffinity group, and social media accounts within a predetermineddistance 620 of the centroid 650 are members of a third affinity group.

The affinity group identifier 510 may determine the distance between asocial media account's position in n-dimensional space 660 and aposition of the closest centroid among centroids 630, 640, and 650 usinga Euclidean distance or using any other metric. The affinity groupidentifier 510 may determine a closeness value for a particular socialmedia account 660 using the determined distance, as discussed herein.

FIG. 7 depicts exemplary methods in accordance with aspects of theinvention. The steps of the method may be performed in the computersystem of FIG. 1, the cloud computing environment of FIG. 2, theenvironment of FIG. 4, and the program module of FIG. 5 and aredescribed with reference to the elements and steps described withrespect to FIGS. 1, 2, 4, and 5.

At step 700, the system gathers social media information and content. Inembodiments, as described with respect to FIG. 5, step 700 may beperformed by the social media information and content gatherer 500 ofthe compromised account detection program module 420 running on theserver 410.

At step 710, the system analyzes the social media information andcontent gathered at step 700 to determine affinity groups. Inembodiments, as described with respect to FIG. 5, step 710 may beperformed by the affinity group identifier 510 of the compromisedaccount detection program module 420 running on the server 410.

At step 720, the system analyzes a new social media post to determine ascore, using the affinity groups determined at step 710 and the socialmedia information and content gathered at step 700. In embodiments, asdescribed with respect to FIG. 5, step 720 may be performed by the newsocial media post analyzer 520 of the compromised account detectionprogram module 420 running on the server 410.

At step 730, the system determines whether or not a social media accountthat posted the new social media post analyzed at step 720 is likely tobe compromised. In embodiments, as described with respect to FIG. 5,step 730 may be performed by the compromised account detector 530 of thecompromised account detection program module 420 running on the server410. If it is determined in step 730 that the social media account isnot likely to be compromised, the flow proceeds to step 750, andprocessing ends. On the other hand, if it is determined in step 730 thatthe social media account is likely to be compromised, the flow proceedsto step 740.

At step 740, the system sends a notification to an account owner of thesocial media account, a social media network operator, or to the socialmedia network or platform associated with the account, indicating thatthe account is likely to be compromised. In embodiments, as describedwith respect to FIG. 5, step 740 may be performed by the compromisedaccount detector 530 of the compromised account detection program module420 running on the server 410. The flow then proceeds to step 750, andprocessing ends.

According to another embodiment, the system may detect newly createdsocial media accounts that were created to distribute malicious content.The system may use the limited information available regarding the newlycreated social media accounts to score the accounts against affinitygroups, including information such as geolocation information (e.g., IPaddresses or user-specified information), account creation date andtime, numbers of friends and followers, and types of information shared(e.g., a level of similarity with respect to information shared by otheraccounts). Additionally, the system may determine that newly createdaccounts are members of a new account affinity group (e.g., accountsthat are less than 10 days old). Since most newly created accounts havemade few posts, a first post including a link to a website without anyadditional context may be determined to be likely connected to acompromised account. Weight factors may be determined using informationsuch as a time since a social media account was created. Thresholds fordetermining that a social media account is likely compromised may belower for newly created social media accounts. These thresholds may beadjusted upwards as the age of the social media account increases.

In embodiments, a service provider could offer to perform the processesdescribed herein. In this case, the service provider can create,maintain, deploy, support, etc., the computer infrastructure thatperforms the process steps of the invention for one or more customers.These customers may be, for example, any business that uses cloudcomputing technology. In return, the service provider can receivepayment from the customer(s) under a subscription and/or fee agreementand/or the service provider can receive payment from the sale ofadvertising content to one or more third parties.

In still additional embodiments, the invention provides acomputer-implemented method, via a network. In this case, a computerinfrastructure, such as computer system/server 12 (FIG. 1), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system/server 12(as shown in FIG. 1), from a computer-readable medium; (2) adding one ormore computing devices to the computer infrastructure; and (3)incorporating and/or modifying one or more existing systems of thecomputer infrastructure to enable the computer infrastructure to performthe processes of the invention.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method for detecting a compromised social mediaaccount, the method comprising: receiving, by a computing device, socialmedia content corresponding to a plurality of social media accounts;determining, by the computing device, a plurality of affinity groups,each including two or more social media accounts from the plurality ofsocial media accounts, based upon the received social media content;determining, by the computing device, whether or not a particular socialmedia account of the plurality of social media accounts is compromisedusing the received social media content and the determined plurality ofaffinity groups, based on a correlation between a new post made by theparticular social media account and posts made by other social mediaaccounts that are members of one or more same affinity groups as theparticular social media account, including determining a score for thenew post made by the particular social media account based on thecorrelation with the posts made by the other social media accounts thatare members of one or more same affinity groups as the particular socialmedia account, wherein the score represents a likelihood of the new posthaving been made by an owner of the particular social media account; andin response to determining that the particular social media account iscompromised, based on the score being lower than a predeterminedthreshold, the computing device providing a notification indicating thatthe particular social media account is compromised.
 2. The methodaccording to claim 1, wherein the determining the plurality of affinitygroups comprises: determining data associated with each of a pluralityof dimensions from the received social media content; and for each ofthe plurality of dimensions, for each of the plurality of social mediaaccounts, scoring the social media account using the determined dataassociated with the dimension for the social media account.
 3. Themethod according to claim 2, wherein the determining the plurality ofaffinity groups further comprises: for each of the plurality of socialmedia accounts, determining a point in n-dimensional space occupied bythe social media account based upon the score for the social mediaaccount for each of the plurality of dimensions; and determining theplurality of affinity groups based on distances between the plurality ofsocial media accounts in the n-dimensional space.
 4. The methodaccording to claim 3, wherein social media accounts within apredetermined threshold distance of a centroid of one of the pluralityof affinity groups are determined to be members of the affinity group.5. The method according to claim 1, wherein the notification indicatingthat the particular social media account is compromised is a pushnotification to a mobile device.
 6. The method according to claim 1,wherein in response to determining that the particular social mediaaccount is compromised, the computing device is further configured toblock use of the particular social media account.
 7. The methodaccording to claim 1, further comprising: determining, by the computingdevice, a plurality of content entities in the new post, including alink, a picture, and text; for each of plurality of content entities,determining, by the computing device, a sub-score based on a correlationbetween the content entity and content entities in the posts made by theother social media accounts that are members of one or more sameaffinity groups as the particular social media account; and determining,by the computing device, the score for the new post based on thesub-scores.
 8. A computer program product comprising a computer readablestorage medium having program instructions embodied therewith, theprogram instructions executable by a computing device to cause thecomputing device to: receive social media content corresponding to aplurality of social media accounts across a plurality of social medianetworks; determine a plurality of affinity groups based upon thereceived social media content; determine whether or not a particularsocial media account of the plurality of social media accounts iscompromised using the received social media content and the determinedplurality of affinity groups, by determining a score for a new post madeby the particular social media account based on a correlation with postsmade by other social media accounts that are members of one or more sameaffinity groups as the particular social media account, wherein thescore represents a likelihood of the new post having been made by anowner of the particular social media account; and in response todetermining that the particular social media account is compromised,based on the score being lower than a predetermined threshold, provide anotification indicating that the particular social media account iscompromised.
 9. The computer program product according to claim 8,wherein the determining the plurality of affinity groups comprises:determining data associated with each of a plurality of dimensions fromthe received social media content; and for each of the plurality ofdimensions, for each of the plurality of social media accounts, scoringthe social media account using the determined data associated with thedimension for the social media account.
 10. The computer program productaccording to claim 9, wherein the determining the plurality of affinitygroups further comprises: for each of the plurality of social mediaaccounts, determining a point in n-dimensional space occupied by thesocial media account based upon the score for the social media accountfor each of the plurality of dimensions; and determining the pluralityof affinity groups based on distances between the plurality of socialmedia accounts in the n-dimensional space.
 11. The computer programproduct according to claim 10, wherein social media accounts within apredetermined threshold distance of a centroid of one of the pluralityof affinity groups are determined to be members of the affinity group.12. The computer program product according to claim 8, wherein thenotification indicating that the particular social media account iscompromised is a push notification to a mobile device.
 13. The computerprogram product according to claim 8, the program instructions furthercausing the computing device to: in response to determining that theparticular social media account is compromised, block use of theparticular social media account.
 14. A system comprising: a hardwareprocessor, a computer readable memory, and a computer readable storagemedium associated with a computer device; program instructions of asocial media content receiver configured to receive social media contentcorresponding to a plurality of social media accounts across a pluralityof social media networks; program instructions of an affinity groupdeterminer configured to determine a plurality of affinity groups, eachincluding two or more social media accounts from the plurality of socialmedia accounts, based upon the received social media content; andprogram instructions of a compromised account determiner configured todetermine whether or not a particular social media account of theplurality of social media accounts is compromised using the receivedsocial media content and the determined plurality of affinity groups, bydetermining a score for a new post made by the particular social mediaaccount based on a correlation with posts made by other social mediaaccounts that are members of one or more same affinity groups as theparticular social media account, wherein the score represents alikelihood of the new post having been made by an owner of theparticular social media account, wherein the compromised accountdeterminer, in response to determining that the particular social mediaaccount is compromised, based on the score being lower than apredetermined threshold, is configured to provide a notificationindicating that the particular social media account is compromised. 15.The system according to claim 14, wherein the affinity group determineris further configured to: determine data associated with each of aplurality of dimensions from the received social media content; and foreach of the plurality of dimensions, for each of the plurality of socialmedia accounts, score the social media account using the determined dataassociated with the dimension for the social media account.
 16. Thesystem according to claim 15, wherein the affinity group determiner isfurther configured to: for each of the plurality of social mediaaccounts, determine a point in n-dimensional space occupied by thesocial media account based upon the score for the social media accountfor each of the plurality of dimensions; and determine the plurality ofaffinity groups based on distances between the plurality of social mediaaccounts in the n-dimensional space.
 17. The system according to claim14, wherein the notification indicating that the particular social mediaaccount is compromised is a push notification to a mobile device. 18.The system according to claim 14, wherein the compromised accountdeterminer is further configured to: in response to determining that theparticular social media account is compromised, block use of theparticular social media account.